Dataset Information

Impact of Changes in Chain Restaurant Calories over Time on Obesity Risk.

ABSTRACT:

Background

Prior research on the restaurant environment and obesity risk is limited by cross-sectional data and a focus on specific geographic areas.

Objective

To measure the impact of changes in chain restaurant calories over time on body mass index (BMI).

Design

We used a first-difference model to examine whether changes from 2012 to 2015 in chain restaurant calories per capita were associated with percent changes in BMI. We also examined differences by race and county income, restaurant type, and initial body weight categories.

Setting

USA (207 counties across 39 states).

Participants

447,873 adult patients who visited an athenahealth medical provider in 2012 and 2015 where BMI was measured.

Main outcomes measured

Percent change in objectively measured BMI from 2012 to 2015.

Results

Across all patients, changes in chain restaurant calories per capita were not associated with percent changes in BMI. For Black or Hispanic adults, a 10% increase in exposure to chain restaurant calories per capita was associated with a 0.16 percentage-point increase in BMI (95% CI 0.03, 0.30). This translates into a predicted weight increase of 0.89 pounds (or a 0.53% BMI increase) for an average weight woman at the 90th percentile of increases in the restaurant environment from 2012 to 2015 versus an increase 0.39 pounds (or 0.23% BMI increase) at the 10th percentile. Greater increases in exposure to chain restaurant calories also significantly increased BMI for Black or Hispanic adults receiving healthcare services in lower-income counties (0.26, 95% CI 0.04, 0.49) and with overweight/obesity (0.16, 95% CI 0.04, 0.29).

Limitations

Generalizability to non-chain restaurants is unknown and the sample of athenahealth patients is relatively homogenous.

Conclusions

Increased exposure to chain restaurant calories per capita was associated with increased weight gain among Black or Hispanic adults.

SUBMITTER: Bleich SN

PROVIDER: S-EPMC7300171 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ImportanceRestaurants spend billions of dollars on marketing. However, little is known about the association between restaurant marketing and obesity risk in adults.ObjectiveTo examine associations between changes in per capita county-level restaurant advertising spending over time and changes in objectively measured body mass index (BMI) for adult patients.Design, setting, and participantsThis cohort study used regression models with county fixed effects to examine associations between changes in per capita county-level (370 counties across 44 states) restaurant advertising spending over time with changes in objectively measured body mass index (BMI) for US adult patients from 2013 to 2016. Different media types and restaurant types were analyzed together and separately. The cohort was derived from deidentified patient data obtained from athenahealth. The final analytic sample included 5 987 213 patients, and the analysis was conducted from March 2018 to November 2019.ExposurePer capita county-level chain restaurant advertising spending.Main outcomes and measuresIndividual-level mean BMI during the quarter.ResultsThe included individuals were generally older (37.1% older than 60 years), female (56.8%), and commercially insured (53.5%). For the full population of 29 285 920 person-quarters, there was no association between changes in all restaurant advertising per capita (all media types, all restaurants) and changes in BMI. However, restaurant advertising spending was positively associated with weight gain for patients in low-income counties but not in high-income counties. A $1 increase in quarterly advertising per capita across all media and restaurant types was associated with a 0.053-unit increase in BMI (95% CI, 0.001-0.102) for patients in low-income counties, corresponding to a 0.12% decrease in BMI at the 10th percentile of changes in county advertising spending vs a 0.12% increase in BMI at the 90th percentile.Conclusions and relevanceThe results of this study suggest that restaurant advertising is associated with modest weight gain among adult patients in low-income counties. To date, there has been no public policy action or private sector action to limit adult exposure to unhealthy restaurant advertising. Efforts to decrease restaurant advertising in low-income communities should be intensified and rigorously evaluated to understand their potential for increasing health equity.

Project description:To investigate temporal trends in coronavirus disease 2019 (COVID-19)-related outcomes and to evaluate whether the impacts of potential risk factors and disparities changed over time, we conducted a retrospective cohort study with 249 075 patients tested or treated for COVID-19 at Michigan Medicine (MM), from 10 March 2020 to 3 May 2021. Among these patients, 26 289 were diagnosed with COVID-19. According to the calendar time in which they first tested positive, the COVID-19-positive cohort were stratified into three-time segments (T1: March–June, 2020; T2: July–December, 2020; T3: January–May, 2021). Potential risk factors that we examined included demographics, residential-level socioeconomic characteristics and preexisting comorbidities. The main outcomes included COVID-19-related hospitalisation and intensive care unit (ICU) admission. The hospitalisation rate for COVID-positive patients decreased from 36.2% in T1 to 14.2% in T3, and the ICU admission rate decreased from 16.9% to 2.9% from T1 to T3. These findings confirm that COVID-19-related hospitalisation and ICU admission rates were decreasing throughout the pandemic from March 2020 to May 2021. Black patients had significantly higher (compared to White patients) hospitalisation rates (19.6% vs. 11.0%) and ICU admission rates (6.3% vs. 2.8%) in the full COVID-19-positive cohort. A time-stratified analysis showed that racial disparities in hospitalisation rates persisted over time and the estimates of the odds ratios (ORs) stayed above unity in both unadjusted [full cohort: OR = 1.98, 95% confidence interval (CI) (1.79, 2.19); T1: OR = 1.70, 95% CI (1.36, 2.12); T2: OR = 1.40, 95% CI (1.17, 1.68); T3: OR = 1.55, 95% CI (1.29, 1.86)] and adjusted analysis, accounting for differences in demographics, socioeconomic status, and preexisting comorbid conditions (full cohort: OR = 1.45, 95% CI (1.25, 1.68); T1: OR = 1.26, 95% CI (0.90, 1.76); T2: OR = 1.29, 95% CI (1.01, 1.64); T3: OR = 1.29, 95% CI (1.00, 1.67)).